Andrew McCallum
Cited by
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Conditional random fields: Probabilistic models for segmenting and labeling sequence data
J Lafferty, A McCallum, FCN Pereira
A comparison of event models for naive bayes text classification
A McCallum, K Nigam
AAAI-98 workshop on learning for text categorization 752 (1), 41-48, 1998
Text classification from labeled and unlabeled documents using EM
K Nigam, AK McCallum, S Thrun, T Mitchell
Machine learning 39, 103-134, 2000
Mallet: A machine learning for languagetoolkit
AK McCallum
http://mallet. cs. umass. edu, 2002
An introduction to conditional random fields
C Sutton, A McCallum
Foundations and Trends® in Machine Learning 4 (4), 267-373, 2012
Energy and policy considerations for deep learning in NLP
E Strubell, A Ganesh, A McCallum
arXiv preprint arXiv:1906.02243, 2019
Optimizing semantic coherence in topic models
D Mimno, H Wallach, E Talley, M Leenders, A McCallum
Proceedings of the 2011 conference on empirical methods in natural language …, 2011
Maximum entropy Markov models for information extraction and segmentation.
A McCallum, D Freitag, FCN Pereira
Icml 17 (2000), 591-598, 2000
Topics over time: a non-markov continuous-time model of topical trends
X Wang, A McCallum
Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006
Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons
A McCallum, W Li
Toward optimal active learning through monte carlo estimation of error reduction
N Roy, A McCallum
ICML, Williamstown 2, 441-448, 2001
Efficient clustering of high-dimensional data sets with application to reference matching
A McCallum, K Nigam, LH Ungar
Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000
Modeling relations and their mentions without labeled text
S Riedel, L Yao, A McCallum
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010
Using maximum entropy for text classification
K Nigam, J Lafferty, A McCallum
IJCAI-99 workshop on machine learning for information filtering 1 (1), 61-67, 1999
Automating the construction of internet portals with machine learning
AK McCallum, K Nigam, J Rennie, K Seymore
Information Retrieval 3, 127-163, 2000
Employing EM and Pool-Based Active Learning for Text Classification.
A McCallum, K Nigam
ICML 98, 350-358, 1998
Distributional clustering of words for text classification
LD Baker, AK McCallum
Proceedings of the 21st annual international ACM SIGIR conference on …, 1998
Learning to extract symbolic knowledge from the World Wide Web
M Craven, D DiPasquo, D Freitag, A McCallum, T Mitchell, K Nigam, ...
AAAI/IAAI 3 (3.6), 2, 1998
Bow: A toolkit for statistical language modeling, text retrieval, classification and clustering
AK McCallum
CMU: Pittsburgh, PA, 1996
Rethinking LDA: Why priors matter
H Wallach, D Mimno, A McCallum
Advances in neural information processing systems 22, 2009
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